National Heart Foundation of Australia: position statement on coronary artery calcium scoring for the primary prevention of cardiovascular disease in Australia

Myosteatosis is associated with coronary artery calcification in patients with type 2 diabetes

BACKGROUND

Myosteatosis, rather than low muscle mass, is the primary etiologic factor of sarcopenia in patients with type 2 diabetes mellitus (T2DM). Myosteatosis may lead to a series of metabolic dysfunctions, such as insulin resistance, systematic inflammation, and oxidative stress, and all these dysfunctions are closely associated with the acceleration of T2DM and atherosclerosis.

AIM

To investigate the association between myosteatosis and coronary artery calcification (CAC) in patients with T2DM.

METHODS

Patients with T2DM, who had not experienced major cardiovascular events and had undergone both abdominal and thoracic computed tomography (CT) scans, were included. The mean skeletal muscle attenuation was assessed using abdominal CT images at the L3 level. The CAC score was determined from thoracic CT images using the Agatston scoring method. Myosteatosis was diagnosed according to Martin's criteria. Severe CAC (SCAC) was defined when the CAC score exceeded 300. Logistic regression and decision tree analyses were performed.

RESULTS

A total of 652 patients with T2DM were enrolled. Among them, 167 (25.6%) patients had SCAC. Logistic regression analysis demonstrated that myosteatosis, age, duration of diabetes, cigarette smoking, and alcohol consumption were independent risk factors of SCAC. Myosteatosis was significantly associated with an increased risk of SCAC (OR = 2.381, P = 0.003). The association between myosteatosis and SCAC was significant in the younger patients (OR = 2.672, 95%CI: 1.477-4.834, P = 0.002), but not the older patients (OR = 1.456, 95%CI: 0.863-2.455, P = 0.188), and was more prominent in the population with lower risks of atherosclerosis. The decision tree analyses prioritized older age as the primary variable for SCAC. In older patients, cigarette smoking was the main contributing factor for SCAC, while in younger patients, it was myosteatosis.

CONCLUSION

Myosteatosis is a novel risk factor for atherosclerosis in patients with T2DM, especially in the population with younger ages and fewer traditional risk factors.

Social, Geographical and Income Inequality as Demonstrated by the Coronary Calcium Score: An Ecological Study in Sydney, Australia

BACKGROUND

The coronary calcium score is a non-invasive biomarker of coronary artery disease. The concept of "arterial age" transforms the coronary calcium score to an expected age based on the degree of coronary atherosclerosis. This study aimed to investigate the relationship of socioeconomic status with the burden of coronary artery disease within Sydney, Australia.

METHODS

This was an ecological study at the postcode level of patients aged 45 and above who had completed a CT coronary calcium scan within New South Wales (NSW), Australia from January 2012 to December 2020. Arterial age difference was calculated as arterial age minus chronological age. Socioeconomic data was obtained for median income, Index of Relative Socio-economic Advantage and Disadvantage (IRSAD) score and median property price. Linear regression was used for analysis.

RESULTS

There were 17,102 patients across 325 postcodes within NSW, comprising 9129 males with a median arterial age difference of 7 years and 7972 females with -9 years. Income, IRSAD score and property price each had an inverse relationship with arterial age difference (p-values < 0.05).

CONCLUSIONS

Income, socioeconomic status and local property prices are significantly correlated with premature coronary aging. Healthcare resource allocation and prevention should target the inequalities identified to reduce the burden of coronary artery disease.

The cost-effectiveness of coronary calcium score-guided statin therapy initiation for Australians with family histories of premature coronary artery disease

OBJECTIVES

To compare the cost-effectiveness of coronary artery calcium (CAC) score-guided statin therapy criteria and American College of Cardiology/American Heart Association (ACC/AHA) guidelines (10-year pooled cohort equation [PCE] risk ≥ 7.5%) with selection according to Australian guidelines (5-year absolute cardiovascular disease risk [ACVDR] ≥ 10%), for people with family histories of premature coronary artery disease.

STUDY DESIGN, SETTING

Markov microsimulation state transition model based on data from the Coronary Artery calcium score: Use to Guide management of Hereditary Coronary Artery Disease (CAUGHT-CAD) trial and transition probabilities derived from published statin prescribing and adherence outcomes and clinical data.

PARTICIPANTS

1083 people with family histories of premature coronary artery disease but no symptomatic cardiovascular disease.

MAIN OUTCOME MEASURES

Relative cost-effectiveness over fifteen years, from the perspective of the Australian health care system, compared with usual care (Australian guidelines), assessed as incremental cost-effectiveness ratios (ICERs), with a notional willingness-to-pay threshold of $50 000 per quality-adjusted life-year (QALY) gained.

RESULTS

Applying the Australian guidelines, 77 people were eligible for statin therapy (7.1%); with ACVDR 5-year risk ≥ 2% and CAC score > 0, 496 people (46%); with ACVDR 5-year risk ≥ 2% and CAC score ≥ 100, 155 people (14%); and with the ACC/AHA guidelines, 256 people (24%). The ICERs for CAC-guided selection were $33 108 (CAC ≥ 100) and $53 028 per QALY gained (CAC > 0); the ACC/AHA guidelines approach (ICER, $909 241 per QALY gained) was not cost-effective. CAC score-guided selection (CAC ≥ 100) was cost-effective for people with 5-year ACVDR of at least 5%.

CONCLUSION

Expanding the number of people at low to intermediate CVD risk eligible for statin therapy should selectively target people with subclinical atherosclerosis identified by CAC screening. This approach can be more cost-effective than simply lowering treatment eligibility thresholds.

Contemporary Chest Pain Evaluation: The Australian Case for Cardiac CT

Computed tomography coronary angiography (CTCA) is a non-invasive diagnostic modality that provides a comprehensive anatomical assessment of the coronary arteries and coronary atherosclerosis, including plaque burden, composition and morphology. The past decade has witnessed an increase in the role of CTCA for evaluating patients with both stable and acute chest pain, and recent international guidelines have provided increasing support for a first line CTCA diagnostic strategy in select patients. CTCA offers some advantages over current functional tests in the detection of obstructive and non-obstructive coronary artery disease, as well as for ruling out obstructive coronary artery disease. Recent randomised trials have also shown that CTCA improves prognostication and guides the use of guideline-directed preventive therapies, leading to improved clinical outcomes. CTCA technology advances such as fractional flow reserve, plaque quantification and perivascular fat inflammation potentially allow for more personalised risk assessment and targeted therapies. Further studies evaluating demand, supply, and cost-effectiveness of CTCA for evaluating chest pain are required in Australia. This discussion paper revisits the evidence supporting the use of CTCA, provides an overview of its implications and limitations, and considers its potential role for chest pain evaluation pathways in Australia.

Major Global Coronary Artery Calcium Guidelines

This review summarizes the framework behind global guidelines of coronary artery calcium (CAC) in atherosclerotic cardiovascular disease risk assessment, for applications in both the clinical setting and preventive therapy. By comparing similarities and differences in recommendations, this review identifies most notable common features for the application of CAC presented by different cardiovascular societies across the world. Guidelines included from North America are as follows: 1) the 2019 American College of Cardiology/American Heart Association Guideline on the Primary Prevention of Cardiovascular Disease; and 2) the 2021 Canadian Cardiovascular Society Guidelines for the Management of Dyslipidemia for Prevention of Adult Cardiovascular Disease. The authors also included European guidelines: 1) the 2019 European Society for Cardiology/European Atherosclerosis Society Guidelines for the Management of Dyslipidemias; and 2) the 2016 National Institute for Health and Care Excellence Clinical Guidelines. In this comparison, the authors also discuss: 1) the Cardiac Society of Australia and New Zealand Guidelines on CAC; 2) the Chinese Society of Cardiology Guidelines; and 3) the Japanese Atherosclerosis Society Guidelines for Prevention of Atherosclerotic Cardiovascular Diseases. Last, they include statements made by specialty societies including the National Lipid Association, Society of Cardiovascular Computed Tomography, and U.S. Preventive Services Task Force. Utilizing an in-depth review of clinical evidence, these guidelines emphasize the importance of CAC in the primary and secondary prevention of atherosclerotic cardiovascular disease. International guidelines all empower a dynamic clinician-patient relationship and advocate for individualized discussions regarding disease management and pharmacotherapy treatment. Some differences in precise coronary artery calcium score intervals, risk cut points, treatment thresholds, and stratifiers of specific patient subgroups do exist. However, international guidelines employ more similarities than differences from both a clinical and functional perspective. Understanding the parallels among international coronary artery calcium guidelines is essential for clinicians to correctly adjudicate personalized statin and aspirin therapy and further medical management.

Evaluation of an artificial intelligence coronary artery calcium scoring model from computed tomography

OBJECTIVES

Coronary artery calcium (CAC) scores derived from computed tomography (CT) scans are used for cardiovascular risk stratification. Artificial intelligence (AI) can assist in CAC quantification and potentially reduce the time required for human analysis. This study aimed to develop and evaluate a fully automated model that identifies and quantifies CAC.

METHODS

Fully convolutional neural networks for automated CAC scoring were developed and trained on 2439 cardiac CT scans and validated using 771 scans. The model was tested on an independent set of 1849 cardiac CT scans. Agatston CAC scores were further categorised into five risk categories (0, 1-10, 11-100, 101-400, and > 400). Automated scores were compared to the manual reference standard (level 3 expert readers).

RESULTS

Of 1849 scans used for model testing (mean age 55.7 ± 10.5 years, 49% males), the automated model detected the presence of CAC in 867 (47%) scans compared with 815 (44%) by human readers (p = 0.09). CAC scores from the model correlated very strongly with the manual score (Spearman's r = 0.90, 95% confidence interval [CI] 0.89-0.91, p < 0.001 and intraclass correlation coefficient = 0.98, 95% CI 0.98-0.99, p < 0.001). The model classified 1646 (89%) into the same risk category as human observers. The Bland-Altman analysis demonstrated little difference (1.69, 95% limits of agreement: -41.22, 44.60) and there was almost excellent agreement (Cohen's κ = 0.90, 95% CI 0.88-0.91, p < 0.001). Model analysis time was 13.1 ± 3.2 s/scan.

CONCLUSIONS

This artificial intelligence-based fully automated CAC scoring model shows high accuracy and low analysis times. Its potential to optimise clinical workflow efficiency and patient outcomes requires evaluation.

KEY POINTS

• Coronary artery calcium (CAC) scores are traditionally assessed using cardiac computed tomography and require manual input by human operators to identify calcified lesions. • A novel artificial intelligence (AI)-based model for fully automated CAC scoring was developed and tested on an independent dataset of computed tomography scans, showing very high levels of correlation and agreement with manual measurements as a reference standard. • AI has the potential to assist in the identification and quantification of CAC, thereby reducing the time required for human analysis.

Effect of C1q/TNF-Related Protein 9 on Coronary Artery Calcification: An Observational Study

Coronary artery calcification (CAC) increases the risk of acute coronary syndrome. This study examined the correlation between C1q/TNF-related protein 9 (CTRP9) and CAC and explored CTRP9 as a biomarker for prognosis. We divided 275 patients with coronary heart disease into four groups. In order to balance the baseline confounding factors, propensity score matching (PSM) was performed to match CAC patients with non-CAC patients in a 1:1 ratio. Optical coherence tomography (OCT) calcification scoring was performed in 126 patients with CAC. Moreover, 140 patients who underwent OCT were followed-up for 9 months for analysis of the correlation between CTRP9 levels and clinical prognosis. Based on OCT calcification scores, 126 patients with CAC were divided into the 0–2 and 3–4 groups. Plasma CTRP9 levels were significantly lower in the type 2 diabetes mellitus (T2DM), CAC and CAC with T2DM groups than in the control group. CTRP9 played roles as a protective factor and potential predictor in CAC severity. The AUC of the OCT calcification score 3–4 group predicted by the plasma CTRP9 level was 0.766. During the follow-up period, the cumulative event-free survival rate was significantly lower in the low-level CTRP9 (L-CTRP9) group than in the high-level (H-CTRP9) group, and the incidence of major endpoint events was significantly higher in the L-CTRP9 group than in the H-CTRP9 group. CTRP9 can be a valuable biomarker for CAC occurrence and severity and can predict patients’ clinical prognosis.